OpenRaiser/Intern-Atlas huggingface dataset:
Toward Crowdsourced User Studies for Software Evaluation
Venue: arXiv cs.HC 2016
Year: 2016

This work-in-progress paper describes a vision, i.e., that of fast and reliable software user experience studies conducted with the help from the crowd. Commonly, user studies are controlled in-lab activities that require the instruction, monitoring, interviewing and compensation of a number of participants that are typically hard to recruit. The goal of this work is to study which user study methods can instead be crowdsourced to generic audiences to enable the conduct of user studies without the need for expensive lab experiments. The challenge is understanding how to conduct crowdsourced studies without giving up too many of the guarantees in-lab settings are able to provide.
Subset Sum Problems With Digraph Constraints
Venue: arXiv cs.CC 2016
Year: 2016

We introduce and study four optimization problems that generalize the well-known subset sum problem. Given a node-weighted digraph, select a subset of vertices whose total weight does not exceed a given budget. Some additional constraints need to be satisfied. The (weak resp.) digraph constraint imposes that if (all incoming nodes of resp.) a node $x$ belongs to the solution, then the latter comprises all its outgoing nodes (node $x$ itself resp.). The maximality constraint ensures that a solution cannot be extended without violating the budget or the (weak) digraph constraint. We study the complexity of these problems and we present some approximation results according to the type of digraph given in input, e.g. directed acyclic graphs and oriented trees. Key words. Subset Sum, Maximal problems, digraph constraints, complexity, directed acyclic graphs, oriented trees, PTAS.
Modelling simultaneous broadcasting by level-disjoint partitions
Venue: arXiv cs.DM 2016
Year: 2016

Simultaneous broadcasting of multiple messages from the same source vertex in synchronous networks is considered under restrictions that each vertex receives at most one message in a unit time step, every received message can be sent out only in the next time step, no message is sent to already informed vertex. The number of outgoing messages in unrestricted, messages have unit length, and we assume full-duplex mode. In [9] we developed a concept of level-disjoint partitions to study simultaneous broadcasting under this model. In this work we consider the optimal number of level-disjoint partitions. We also provide a necessary condition in terms of eccentricity and girth on existence of $k$ $v$-rooted level-disjoint partitions of optimal height. In particular, we provide a structural characterization of graphs admitting two level-disjoint partitions with the same root.
Cost-efficient Scheduling on Machines from the Cloud
Venue: arXiv cs.DS 2016
Year: 2016

We consider a scheduling problem where machines need to be rented from the cloud in order to process jobs. There are two types of machines available which can be rented for machine-type dependent prices and for arbitrary durations. However, a machine-type dependent setup time is required before a machine is available for processing. Jobs arrive online over time, have machine-type dependent sizes and have individual deadlines. The objective is to rent machines and schedule jobs so as to meet all deadlines while minimizing the rental cost. Since we observe the slack of jobs to have a fundamental influence on the competitiveness, we study the model when instances are parameterized by their (minimum) slack. An instance is called to have a slack of $β$ if, for all jobs, the difference between the job's release time and the latest point in time at which it needs to be started is at least $β$. While for $β< s$ no finite competitiveness is possible, our main result is an $O(\frac{c}{\varepsilon} + \frac{1}{\varepsilon^3})$-competitive online algorithm for $β= (1+\varepsilon)s$ with $\frac{1}{s} \leq \varepsilon \leq 1$, where $s$ and $c$ denotes the largest setup time and the cost ratio of the machine-types, respectively. It is complemented by a lower bound of $Ω(\frac{c}{\varepsilon})$.
SDFog: A Software Defined Computing Architecture for QoS Aware Service Orchestration over Edge Devices
Venue: arXiv cs.NI 2016
Year: 2016

Cloud computing revolutionized the information technology (IT) industry by offering dynamic and infinite scaling, on-demand resources and utility-oriented usage. However, recent changes in user traffic and requirements have exposed the shortcomings of cloud computing, particularly the inability to deliver real-time responses and handle massive surge in data volumes. Fog computing, that brings back partial computation load from the cloud to the edge devices, is envisioned to be the next big change in computing, and has the potential to address these challenges. Being a highly distributed, loosely coupled and still in the emerging phase, standardization, quality-of-service management and dynamic adaptability are the key challenges faced by fog computing research fraternity today. This article aims to address these issues by proposing a service-oriented middleware that leverages the convergence of cloud and fog computing along with software defined networking (SDN) and network function virtualization (NFV) to achieve the aforementioned goals. The proposed system, called "Software Defined Fog" (SDFog), abstracts connected entities as services and allows applications to orchestrate these services with end-to-end QoS requirements. A use-case showing the necessity of such a middleware has been presented to show the efficacy of the SDN-based QoS control over the Fog. This article aims at developing an integrated system to realize the software-defined control over fog infrastructure.
Volume Raycasting mit OpenCL
Venue: arXiv cs.GR 2016
Year: 2016

This German paper was written entirely at the University of Duisburg-Essen in 2011 for a 3D modeling masters course in applied computer science. We publish this paper, thus, interested people can acquire a first impression of the topic "volume raycasting". In addition to writing this paper, we developed a functioning open-source OpenCL raycaster. A video of this raycaster is available: http://www.youtube.com/watch?v=VMMsQnf4zEY. Additionally, we archived and published the complete source code of the raycaster in the Google Code Archive: http://code.google.com/p/gputracer/. If this is no longer the case, those who are interested can also write an email to the author, hence, we can provide the source code. This paper provides an introduction and overview of the topic "volume ray casting with OpenCL". We show how volume data can be loaded, manipulated, and visualized by modern GPUs in real time. In addition, we present basic algorithms and data structures that are necessary for building such a raycaster. Then, we describe how we built a rudimentary raycaster using OpenCL and .NET C#. Furthermore, we analyze different gradient operators (CentralDifference, Sobel3D and Zucker-Hummel) for surface detection and show an evaluation of these with respect to their performance. Finally, we present optimization techniques (hitpoint refinement, adaptive sampling, octrees, and empty-space-skipping) for improving a raycaster.
Object Specific Deep Learning Feature and Its Application to Face Detection
Venue: arXiv cs.CV 2016
Year: 2016

We present a method for discovering and exploiting object specific deep learning features and use face detection as a case study. Motivated by the observation that certain convolutional channels of a Convolutional Neural Network (CNN) exhibit object specific responses, we seek to discover and exploit the convolutional channels of a CNN in which neurons are activated by the presence of specific objects in the input image. A method for explicitly fine-tuning a pre-trained CNN to induce an object specific channel (OSC) and systematically identifying it for the human face object has been developed. Based on the basic OSC features, we introduce a multi-resolution approach to constructing robust face heatmaps for fast face detection in unconstrained settings. We show that multi-resolution OSC can be used to develop state of the art face detectors which have the advantage of being simple and compact.
Test-Bed based Comparison of Single and Parallel TCP and the Impact Of Parallelism on Throughput and Fairness in Heterogenous Networks
Venue: arXiv cs.NI 2016
Year: 2016

Parallel Transport Control Protocol (TCP) has been used to effectively utilize bandwidth for data intensive applications over high Bandwidth-Delay Product (BDP) networks. On the other hand, it has been argued that, a single-based TCP connection with proper modification such as HSTCP can emulate and capture the robustness of parallel TCP and can well replace it. In this work a Comparison between Single-Based and the proposed parallel TCP has been conducted to show the differences in their performance measurements such as throughput performance and throughput ratio, as well as the link sharing Fairness also has been observed to show the impact of using the proposed Parallel TCP on the existing Single-Based TCP connections. The experiment results show that, single-based TCP cannot overcome Parallel TCP especially in heterogeneous networks where the packet losses are common. Furthermore, the proposed parallel TCP does not affect TCP fairness which makes parallel TCP highly recommended to effectively utilize bandwidth for data intensive applications.
Coexistence of Filter Banks and CP-OFDM: What are the Real Gains?
Venue: arXiv cs.IT 2016
Year: 2016

A coexistence scenario between filter bank (FB) based waveforms and legacy Cyclic Prefix-Orthogonal Frequency Division Multiplexing (CP-OFDM) is studied. It is shown that studies available on that matter use a wrong metric to rate the interference between the coexisting systems. Specifically, it is shown that even well spectrally localized FB waveforms interfere at a high level with incumbent CP-OFDM receivers. The presented results invalidate a number of studies in the literature, which stated that FB based waveforms could be very efficiently used to insert communications in parts of spectrum left free by incumbent legacy CP-OFDM users.
Q-Learning with Basic Emotions
Venue: arXiv cs.LG 2016
Year: 2016

Q-learning is a simple and powerful tool in solving dynamic problems where environments are unknown. It uses a balance of exploration and exploitation to find an optimal solution to the problem. In this paper, we propose using four basic emotions: joy, sadness, fear, and anger to influence a Qlearning agent. Simulations show that the proposed affective agent requires lesser number of steps to find the optimal path. We found when affective agent finds the optimal path, the ratio between exploration to exploitation gradually decreases, indicating lower total step count in the long run
Upper Domination: towards a dichotomy through boundary properties
Venue: arXiv cs.DM 2016
Year: 2016

An upper dominating set in a graph is a minimal (with respect to set inclusion) dominating set of maximum cardinality. The problem of finding an upper dominating set is generally NP-hard. We study the complexity of this problem in classes of graphs defined by finitely many forbidden induced subgraphs and conjecture that the problem admits a dichotomy in this family, i.e. it is either NP-hard or polynomial-time solvable for each class in the family. A helpful tool to study the complexity of an algorithmic problem on finitely defined classes of graphs is the notion of boundary classes. However, none of such classes has been identified so far for the upper dominating set problem. In the present paper, we discover the first boundary class for this problem and prove the dichotomy for classes defined by a single forbidden induced subgraph.
Public scientists contributing to local literary fiction. An exploratory analysis
Venue: arXiv cs.DL 2016
Year: 2016

Public scientists (scientists only from now onwards), understood as a member of the teaching and/or research staff of a public university or a public research organization (including humanities and social sciences), benefit the academic community, industry and other social collectives through teaching and research. Active involvement of scientists in culture is part of the richness of developed societies. Some voices in current debates on the evaluation of societal impact and the role of universities towards social development are claiming a refocus from a socioeconomic perspective to also including sociocultural benefits from academiaIn this paper we will focus in one facet of cultural engagement; writing literary fiction. We will narrow our general objective to local activities, due to the interest in the engagement of scientist on this geographic dimension. Do local publishers include the literary work of scientists? Are works written by scientists more likely to be local than works not written by scientists?
Automatically extracting, ranking and visually summarizing the treatments for a disease
Venue: arXiv cs.CL 2016
Year: 2016

Clinicians are expected to have up-to-date and broad knowledge of disease treatment options for a patient. Online health knowledge resources contain a wealth of information. However, because of the time investment needed to disseminate and rank pertinent information, there is a need to summarize the information in a more concise format. Our aim of the study is to provide clinicians with a concise overview of popular treatments for a given disease using information automatically computed from Medline abstracts. We analyzed the treatments of two disorders - Atrial Fibrillation and Congestive Heart Failure. We calculated the precision, recall, and f-scores of our two ranking methods to measure the accuracy of the results. For Atrial Fibrillation disorder, maximum f-score for the New Treatments weighing method is 0.611, which occurs at 60 treatments. For Congestive Heart Failure disorder, maximum f-score for the New Treatments weighing method is 0.503, which occurs at 80 treatments.
Fleet management for autonomous vehicles
Venue: arXiv cs.DS 2016
Year: 2016

The VIPAFLEET project consists in developing models and algorithms for man- aging a fleet of Individual Public Autonomous Vehicles (VIPA). Hereby, we consider a fleet of cars distributed at specified stations in an industrial area to supply internal transportation, where the cars can be used in different modes of circulation (tram mode, elevator mode, taxi mode). One goal is to develop and implement suitable algorithms for each mode in order to satisfy all the requests under an economic point of view by minimizing the total tour length or the makespan. The innovative idea and challenge of the project is to develop and install a dynamic fleet management system that allows the operator to switch between the differ- ent modes within the different periods of the day according to the dynamic transportation demands of the users. We model the underlying online transportation system and propose an according fleet management framework, to handle modes, demands and commands. We propose for each mode appropriate online algorithms and evaluate their performance.
Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking
Venue: arXiv cs.CV 2016
Year: 2016

To help accelerate progress in multi-target, multi-camera tracking systems, we present (i) a new pair of precision-recall measures of performance that treats errors of all types uniformly and emphasizes correct identification over sources of error; (ii) the largest fully-annotated and calibrated data set to date with more than 2 million frames of 1080p, 60fps video taken by 8 cameras observing more than 2,700 identities over 85 minutes; and (iii) a reference software system as a comparison baseline. We show that (i) our measures properly account for bottom-line identity match performance in the multi-camera setting; (ii) our data set poses realistic challenges to current trackers; and (iii) the performance of our system is comparable to the state of the art.
Multi-Tenancy Issues with Service Delivery in Developing Economies: Privacy, Trust and Availability Concerns
Venue: arXiv cs.CY 2016
Year: 2016

Cloud computing is a new paradigm and innovation in the technology service delivery. It is utilized for IT-enabled value creation. The capex-free nature of cloud service delivery renders it very attractive to many SMEs. But it is saddled with multi-tenancy issues; prominent under this study are concerns of privacy, trust and availability. How do end-users trust providers with their sensitive data? How secured and confidential are their corporate assets? Amidst the perennial power outages (a.k.a. Dumsor), what is the acceptable available uptime? We sampled and interviewed cloud service providers (CSPs) as well as end-users in Ghana, a developing economy. We also gleaned through some secondary data to ascertain some operational concerns. The results indicate that security and service level agreements (SLAs) are key concerns in respect of privacy and trust issues. Similarly, perennial power outages and security were key availability concerns. This was expected as end-users use cloud services for mission critical information assets, and so requires high availability. The implications are that the cyber-security concerns ought to be addressed if SMEs in developing economies are to adopt and accept cloud computing resources for IT-enabled competitive advantage.
Animal Classification System: A Block Based Approach
Venue: arXiv cs.CV 2016
Year: 2016

In this work, we propose a method for the classification of animal in images. Initially, a graph cut based method is used to perform segmentation in order to eliminate the background from the given image. The segmented animal images are partitioned in to number of blocks and then the color texture moments are extracted from different blocks. Probabilistic neural network and K-nearest neighbors are considered here for classification. To corroborate the efficacy of the proposed method, an experiment was conducted on our own data set of 25 classes of animals, which consisted of 4000 sample images. The experiment was conducted by picking images randomly from the database to study the effect of classification accuracy, and the results show that the K-nearest neighbors classifier achieves good performance.
Automatic Visual Theme Discovery from Joint Image and Text Corpora
Venue: arXiv cs.CV 2016
Year: 2016

A popular approach to semantic image understanding is to manually tag images with keywords and then learn a mapping from vi- sual features to keywords. Manually tagging images is a subjective pro- cess and the same or very similar visual contents are often tagged with different keywords. Furthermore, not all tags have the same descriptive power for visual contents and large vocabulary available from natural language could result in a very diverse set of keywords. In this paper, we propose an unsupervised visual theme discovery framework as a better (more compact, efficient and effective) alternative to semantic represen- tation of visual contents. We first show that tag based annotation lacks consistency and compactness for describing visually similar contents. We then learn the visual similarity between tags based on the visual features of the images containing the tags. At the same time, we use a natural language processing technique (word embedding) to measure the seman- tic similarity between tags. Finally, we cluster tags into visual themes based on their visual similarity and semantic similarity measures using a spectral clustering algorithm. We conduct user studies to evaluate the effectiveness and rationality of the visual themes discovered by our unsu- pervised algorithm and obtains promising result. We then design three common computer vision tasks, example based image search, keyword based image search and image labelling to explore potential applica- tion of our visual themes discovery framework. In experiments, visual themes significantly outperforms tags on semantic image understand- ing and achieve state-of-art performance in all three tasks. This again demonstrate the effectiveness and versatility of proposed framework.
Polysemous codes
Venue: arXiv cs.CV 2016
Year: 2016

This paper considers the problem of approximate nearest neighbor search in the compressed domain. We introduce polysemous codes, which offer both the distance estimation quality of product quantization and the efficient comparison of binary codes with Hamming distance. Their design is inspired by algorithms introduced in the 90's to construct channel-optimized vector quantizers. At search time, this dual interpretation accelerates the search. Most of the indexed vectors are filtered out with Hamming distance, letting only a fraction of the vectors to be ranked with an asymmetric distance estimator. The method is complementary with a coarse partitioning of the feature space such as the inverted multi-index. This is shown by our experiments performed on several public benchmarks such as the BIGANN dataset comprising one billion vectors, for which we report state-of-the-art results for query times below 0.3\,millisecond per core. Last but not least, our approach allows the approximate computation of the k-NN graph associated with the Yahoo Flickr Creative Commons 100M, described by CNN image descriptors, in less than 8 hours on a single machine.
Enhancing Channel Assignment Performance in Wireless Mesh Networks Through Interference Mitigation Functions
Venue: arXiv cs.NI 2016
Year: 2016

The notion of Total Interference Degree (TID) is traditionally used to estimate the intensity of prevalent interference in a Multi-RadioMulti-ChannelWirelessMesh Network (MRMC WMN). Numerous Channel Assignment (CA) approaches, linkscheduling algorithms and routing schemes have been proposed for WMNs which rely entirely on the concept of TID estimates. They focus on minimizing TID to create a minimal interference scenario for the network. In our prior works [1] and [2], we have questioned the efficacy of TID estimate and then proposed two reliable interference estimation metrics viz., Channel Distribution Across Links Cost (CDALcost) and Cumulative X-Link-Set Weight (CXLSwt). In this work, we assess the ability of these interference estimation metrics to replace TID as the interferenceminimizing factor in a CA scheme implemented on a grid MRMC WMN. We carry out a comprehensive evaluation on ns-3 and then conclude from the results that the performance of the network increases by 10-15% when the CA scheme uses CXLSwt as the underlying Interference Mitigation Function (IMF) when compared with CA using TID as IMF. We also confirm that CDALcost is not a better IMF than TID and CXLSwt.
Query Optimization Techniques In Graph Databases
Venue: arXiv cs.DB 2016
Year: 2016

Graph databases (GDB) have recently been arisen to overcome the limits of traditional databases for storing and managing data with graph-like structure. Today, they represent a requirement for many applications that manage graph-like data, like social networks. Most of the techniques, applied to optimize queries in graph databases, have been used in traditional databases, distribution systems... or they are inspired from graph theory. However, their reuse in graph databases should take care of the main characteristics of graph databases, such as dynamic structure, highly interconnected data, and ability to efficiently access data relationships. In this paper, we survey the query optimization techniques in graph databases. In particular, we focus on the features they have introduced to improve querying graph-like data.